{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from   fundopt.fundopt import FundTargetRetMinCVaROptimiser, FundTargetRetMinVarianceOptimiser\n",
    "import pandas   as pd\n",
    "import numpy    as np\n",
    "import datetime as dt\n",
    "import cvxpy as cvx\n",
    "import logging"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "start = dt.date(2020, 1, 1)\n",
    "end   = dt.date(2021, 5, 21)\n",
    "holding =  20\n",
    "\n",
    "fund_returns = pd.read_pickle('./{}_{}_{}.pkl'.format(start, end, holding))\n",
    "\n",
    "# Not tradeable\n",
    "fund_returns.drop(['003064'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Look back period from 2020-05-21 00:00:00 to 2021-05-21 00:00:00\n",
      "Top 5 high return funds:\n",
      "002190    0.067913\n",
      "540008    0.066255\n",
      "001643    0.064898\n",
      "001644    0.064492\n",
      "090018    0.064084\n",
      "dtype: float64\n",
      "===============================================================================\n",
      "                                     CVXPY                                     \n",
      "                                    v1.1.12                                    \n",
      "===============================================================================\n",
      "(CVXPY) May 23 02:08:18 PM: Your problem has 3525 variables, 3 constraints, and 1 parameters.\n",
      "(CVXPY) May 23 02:08:19 PM: It is compliant with the following grammars: DCP, DQCP\n",
      "(CVXPY) May 23 02:08:19 PM: CVXPY will first compile your problem; then, it will invoke a numerical solver to obtain a solution.\n",
      "-------------------------------------------------------------------------------\n",
      "                                  Compilation                                  \n",
      "-------------------------------------------------------------------------------\n",
      "(CVXPY) May 23 02:08:19 PM: Compiling problem (target solver=GLPK).\n",
      "(CVXPY) May 23 02:08:19 PM: Reduction chain: Dcp2Cone -> CvxAttr2Constr -> ConeMatrixStuffing -> GLPK\n",
      "(CVXPY) May 23 02:08:19 PM: Applying reduction Dcp2Cone\n",
      "(CVXPY) May 23 02:08:21 PM: Applying reduction CvxAttr2Constr\n",
      "(CVXPY) May 23 02:08:21 PM: Applying reduction ConeMatrixStuffing\n",
      "(CVXPY) May 23 02:10:06 PM: Applying reduction GLPK\n",
      "(CVXPY) May 23 02:10:09 PM: Finished problem compilation (took 1.106e+02 seconds).\n",
      "(CVXPY) May 23 02:10:09 PM: (Subsequent compilations of this problem, using the same arguments, should take less time.)\n",
      "-------------------------------------------------------------------------------\n",
      "                                Numerical solver                               \n",
      "-------------------------------------------------------------------------------\n",
      "(CVXPY) May 23 02:10:09 PM: Invoking solver GLPK  to obtain a solution.\n",
      "-------------------------------------------------------------------------------\n",
      "                                    Summary                                    \n",
      "-------------------------------------------------------------------------------\n",
      "(CVXPY) May 23 02:10:16 PM: Problem status: optimal\n",
      "(CVXPY) May 23 02:10:16 PM: Optimal value: 1.630e+03\n",
      "(CVXPY) May 23 02:10:16 PM: Compilation took 1.106e+02 seconds\n",
      "(CVXPY) May 23 02:10:16 PM: Solver (including time spent in interface) took 6.333e+00 seconds\n",
      "Sell fund 020005 for 44499.00 Yuan\n",
      "Sell fund 163406 for 117108.00 Yuan\n",
      "Buy  fund 000991 for 43855.49 Yuan\n",
      "Buy  fund 001643 for 14897.18 Yuan\n",
      "Buy  fund 001681 for 1721.74 Yuan\n",
      "Buy  fund 001718 for 71400.66 Yuan\n",
      "Buy  fund 090018 for 858.54 Yuan\n",
      "Buy  fund 502023 for 27872.63 Yuan\n",
      "\n"
     ]
    }
   ],
   "source": [
    "lookback_start = dt.date(2020, 5, 21)\n",
    "lookback_end   = dt.date(2021, 5, 21)\n",
    "lookback = pd.bdate_range(lookback_start, lookback_end)\n",
    "\n",
    "print( f\"Look back period from {lookback.min()} to {lookback.max()}\" )\n",
    "print( \"Top 5 high return funds:\")\n",
    "print( fund_returns.reindex(lookback).fillna(0.0).mean(axis=0).sort_values(ascending=False).head() )\n",
    "\n",
    "opt = FundTargetRetMinCVaROptimiser(\n",
    "    targetRet=0.05, \n",
    "    returns=fund_returns)\n",
    "\n",
    "current=pd.Series(dtype=float)\n",
    "current['163406'] = 117108.0\n",
    "current['020005'] = 44499.0\n",
    "\n",
    "solver_options = { \n",
    "    'verbose' : True,\n",
    "    'solver'  : cvx.GLPK,\n",
    " }\n",
    "opt_trade = opt.getOptimalPosition(current, lookbackPeriod=lookback, solver_options=solver_options)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "target_rets = np.arange(0.01, 0.06, 0.001)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "solver_options = { \n",
    "    'verbose' : False,\n",
    "    'solver'  : cvx.GLPK,\n",
    " }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.01 -599.274924450539\n",
      "0.011 -599.2749244505387\n",
      "0.011999999999999999 -599.2749244505387\n",
      "0.012999999999999998 -599.2749244505387\n",
      "0.013999999999999997 -599.2749244505387\n",
      "0.014999999999999996 -599.2749244505387\n",
      "0.015999999999999993 -599.2749244505387\n",
      "0.016999999999999994 -599.2749244505387\n",
      "0.017999999999999995 -599.2744055134986\n",
      "0.018999999999999993 -590.3474598867746\n",
      "0.01999999999999999 -579.090091890192\n",
      "0.02099999999999999 -563.7383460811421\n",
      "0.021999999999999992 -543.9600387640198\n",
      "0.02299999999999999 -523.1217449172261\n",
      "0.023999999999999987 -500.5586086811075\n",
      "0.024999999999999988 -475.78815342330324\n",
      "0.02599999999999999 -449.15138235494356\n",
      "0.02699999999999999 -421.91155459309624\n",
      "0.027999999999999983 -391.7048474770618\n",
      "0.028999999999999984 -359.8572813012188\n",
      "0.029999999999999985 -320.1000177389061\n",
      "0.030999999999999986 -278.3361896573954\n",
      "0.03199999999999998 -235.697988541607\n",
      "0.03299999999999998 -192.8040940005409\n",
      "0.03399999999999998 -149.91019945947508\n",
      "0.03499999999999998 -107.01630491840965\n",
      "0.035999999999999976 -57.17801303783219\n",
      "0.03699999999999998 13.604067303951581\n",
      "0.03799999999999998 97.75876552226532\n",
      "0.03899999999999998 195.50274838148954\n",
      "0.03999999999999997 294.66702476179887\n",
      "0.040999999999999974 393.87835695781746\n",
      "0.041999999999999975 493.0896891538376\n",
      "0.042999999999999976 592.3010213498569\n",
      "0.04399999999999998 691.5123535458779\n",
      "0.04499999999999997 790.7541262789043\n",
      "0.04599999999999997 892.8964471942043\n",
      "0.04699999999999997 1014.857675351157\n",
      "0.047999999999999966 1143.6021918911983\n",
      "0.04899999999999997 1324.433389534323\n",
      "0.04999999999999997 1629.5159884760405\n",
      "0.05099999999999997 2125.8428566009566\n",
      "0.05199999999999997 2737.503201062401\n",
      "0.052999999999999964 3359.5036137536163\n",
      "0.053999999999999965 3984.1862771722135\n",
      "0.054999999999999966 4608.86894059081\n",
      "0.05599999999999996 5238.981208172832\n",
      "0.05699999999999996 5869.241716172857\n",
      "0.05799999999999996 6499.502224172882\n",
      "0.05899999999999996 7129.762732172917\n"
     ]
    }
   ],
   "source": [
    "res = []\n",
    "for ret in target_rets:\n",
    "    opt.set_target_ret_and_rerun(ret, solver_options)\n",
    "    print(ret, opt.cvxProblem.value)\n",
    "    res.append((ret, opt.cvxProblem.value))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = np.array(res)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x22ce4599700>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(data[:, 0], data[:, 1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "final = current.add(opt_trade, fill_value=0.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "final = final[final.abs()>0.1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "from fundopt.fundtsloader import getTSLoader"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "rolled = {}\n",
    "daily = {}\n",
    "for symbol, value in final.iteritems():\n",
    "    loader = getTSLoader(symbol)\n",
    "    loader.load(lookback_start, lookback_end)\n",
    "    ret_ts = loader.getReturnTS(lookback_start, lookback_end)\n",
    "    rolled[symbol] = value * (1.+ret_ts).cumprod()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "backtest = pd.DataFrame.from_dict( rolled )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "backtest.dropna().sum(axis=1).plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1 = pd.read_pickle('2020-01-01_2021-05-21_20.pkl')\n",
    "df2 = pd.read_pickle('2020-01-01_2021-05-21_20_v2.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(343, 3525)"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_symbols = df2.columns.difference(df1.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df2[new_symbols[-10:]].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df2['968012'].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
